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We derive conditions on the learning environment - which encompasses both Bayesian and non-Bayesian processes - ensuring that an efficient allocation of resources is achievable in a dynamic allocation environment where impatient, privately informed agents arrive over time, and where the designer...
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We derive the revenue maximizing allocation of m units among n symmetric agents who have unit demand, and who take costly actions that influence their values before participating in the mechanism. The allocation problem with costly actions can be represented by a reduced form model where agents...
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Arne Ryde Memorial Lectures Series List -- Contents -- About the Arne Ryde Foundation -- Acknowledgments -- 1 Introduction -- 2 The Sequential Assignment of Heterogeneous Objects -- 3 Dynamic Revenue Maximization with Heterogeneous Objects -- 4 The Stochastic and Dynamic Knapsack Model -- 5...
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